Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
We introduce parameterized pattern queries as a new paradigm to extend traditional pattern expressions over sequence databases. A parameterized pattern is essentially a string mad...
Bounded Model Checking (BMC) is an efficient technique applicable to verification of temporal properties of (timed) distributed systems. In this paper we show for the first time ho...
Michal Knapik, Wojciech Penczek, Maciej Szreter, A...
Background: One type of DNA microarray experiment is discovery of gene expression patterns for a cell line undergoing a biological process over a series of time points. Two import...